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· What are some good SAS programming practices for
processing very large data sets?
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Answer Posted / pricil kurian
1) Compressing dataset
2) Using where instead of if as subsetting conditions
3) Deleting the temporary datasets at the end of the program
4) If we use "if..else ..if conditions"..use most occuring
situations first
5)Use keep and drop appropriately to avoid the unneceesary
variable
6).Creattion of index variable
7)Use of array statement
8)Create one byte required numeric variable which we don't
use for calcualting process as charcater..Using this this
variable need 1 byte where numeric variable's minimum
length is 3.
9)Minimize the CPU time that SAS uses by executing the
minimum number of statements in the most efficient
order.
10)Use SQL for code simplification. A single SQL statement
is generally easier to code and understand than a
long series of SORT and DATA steps.
11)Use of data _null_; when we don't need to output into a
new dataset.
12)Use macros for redundant code.
13)When data sets are large and unsorted, the SQL inner
join may beter than SORT and MERGE.
| Is This Answer Correct ? | 8 Yes | 0 No |
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